Equivalent input disturbance‐based model predictive control for Stewart platform system

Abstract The Stewart platform is typically used to simulate vibration response in six degrees of freedom (six‐DOF). However, the influence of the mechanical structure, specifically the coupling between limbs, makes it challenging to dynamically synchronize the motion trajectory. In addition, it is difficult for the Stewart platform to reproduce the input response with high accuracy due to external disturbances and unmodelled dynamics. Spurred by these limitations, this paper introduces a joint space control strategy and presents an equivalent input disturbance‐based model predictive control (EID‐MPC) method for the Stewart platform system. Precisely, the coupling between limbs and external disturbances is considered the total disturbance through the equivalent input disturbance (EID) method. The model predictive controller then incorporates the total disturbance information into the optimization framework to construct the EID‐MPC algorithm. The control system can be divided into two subsystems: the MPC subsystem tracks the input response by solving optimization problems, and the EID subsystem is used to estimate and suppress the total disturbance. Based on the separation principle and the small gain theorem, the system design is simplified, and the stability analysis of the system is provided. Finally, the decoupling performance and comprehensive tracking performance of the EID‐MPC algorithm are verified through simulations and experiments.